Exploring Class Overlap in Classification Challenges: Introducing the R Package

Data Quality Problems

Class Overlapping Problem

• Class overlap occurs when instances of more than one class share a common region in the data space and are not clearly separable

Class Overlapping Problem

• Class overlap occurs when instances of more than one class share a common region in the data space and are not clearly separable

• This overlap can happen due to:

  • Inherent Similarity: Natural similarity between classes

Class Overlapping Problem

• Class overlap occurs when instances of more than one class share a common region in the data space and are not clearly separable

• This overlap can happen due to:

  • Inherent Similarity: Natural similarity between classes

  • Noise: Variability or errors in data collection

Class Overlapping Problem

• Class overlap occurs when instances of more than one class share a common region in the data space and are not clearly separable

• This overlap can happen due to:

  • Inherent Similarity: Natural similarity between classes

  • Noise: Variability or errors in data collection

  • Feature Representation: Insufficient or inadequate features to separate classes

Class Overlapping Problem

• Class overlap occurs when instances of more than one class share a common region in the data space and are not clearly separable

• This overlap can happen due to:

  • Inherent Similarity: Natural similarity between classes

  • Noise: Variability or errors in data collection

  • Feature Representation: Insufficient or inadequate features to separate classes

• It makes it challenging for classifiers to accurately distinguish between classes

Implications of Class Overlap

• Classifiers struggle to correctly classify instances due to overlapping regions

Implications of Class Overlap

• Classifiers struggle to correctly classify instances due to overlapping regions

• Higher error rates occur in areas where classes overlap, leading to more instances being misclassified

Implications of Class Overlap

• Classifiers struggle to correctly classify instances due to overlapping regions

• Higher error rates occur in areas where classes overlap, leading to more instances being misclassified

• If the problem of class overlap is not addressed, models may become overly complex, leading to overfitting issues where the model performs well on training data but poorly on unseen data